{"id":254471,"date":"2023-09-22T05:08:47","date_gmt":"2023-09-22T05:08:47","guid":{"rendered":"https:\/\/imarticus.org\/?p=254471"},"modified":"2023-10-20T13:20:18","modified_gmt":"2023-10-20T13:20:18","slug":"analysis-and-segmentation-with-ai-market-basket-analysis-and-customer-behaviour-analysis","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/analysis-and-segmentation-with-ai-market-basket-analysis-and-customer-behaviour-analysis\/","title":{"rendered":"Analysis and Segmentation with AI: Market Basket Analysis and Customer Behaviour Analysis"},"content":{"rendered":"

Artificial Intelligence (AI) has transformed how organisations assess and segment their clients. With the power of AI, organisations can now analyse customer behaviour and preferences, shopping history, and many more. AI technologies can help business analysts harness all this knowledge to make data-driven decisions.<\/p>\n

Enrolling in an AI ML training and AI learning course<\/a><\/strong> is a great way to enhance your skills in artificial intelligence. This blog will explore two essential techniques of AI in business analysis: Market Basket Analysis and Customer Behavior Analysis.<\/p>\n

Market Basket Analysis<\/h2>\n

Market basket analysis (MBA) is a data mining approach retailers use to find purchase patterns in any retail context. It involves evaluating huge data sets, such as purchase history, to uncover product groups and products likely to be purchased together. MBA is a series of statistical affinity calculations that assist business owners in better understanding \u2013 and ultimately serving \u2013 their customers by identifying purchase trends. In basic terms, MBA looks for what combinations of products most commonly occur together in transactions.<\/p>\n

Leveraging AI for market basket analysis<\/strong><\/h3>\n

Market basket analysis is a data mining technique that identifies co-occurrence patterns and analyses the strength of the link between purchased products. Machine learning experts utilise this unsupervised learning technique to generate data-driven strategies for merchants, enhancing sales. It requires minimum feature engineering and minimal data cleaning.<\/p>\n

By applying AI Association Rule Mining, merchants can boost market basket analysis and cross-selling techniques, increasing assortment efficiency. This analysis can identify which things buyers purchase together, assist companies in locating products together, and propose items customers commonly add to their shopping carts. This strategy also allows firms to deliver customised suggestions to clients.<\/p>\n

Customer Behavior Analysis<\/strong><\/h3>\n

Customer behaviour analysis is a technique of acquiring and analysing data about how customers engage with a firm. It provides insight into customer behaviour, including social trends, frequency patterns, and background variables influencing their decision to buy anything. The study helps organisations identify their target demographic and generate more compelling products and service offers.<\/p>\n

A customer behaviour analysis entails segmenting customers into buyer personas based on their similar interests and analysing each group at their appropriate stage in the customer journey to see how the different personas interact with the organisation. This research delivers insight into the elements that impact audiences and the motives, priorities, and decision-making procedures clients consider during their trips. The results of a customer behaviour study help organisations gain insight into how customers engage with a business and enable them to modify its products or services or marketing to create greater sales.<\/p>\n

Leveraging AI for customer behavior analysis<\/strong><\/h3>\n

Here are some ways businesses are leveraging AI for customer behaviour analysis:<\/strong><\/p>\n